Как объяснить технологические аварии? "Человеческий фактор", социальный конструктивизм и онтологический поворот в изучении неопределенностей беспилотных автомобилей

Abstract

Public discourse about technological accidents is dominated by the popular explanation through the "human factor". It makes the essential assertion that a human, by definition, is prone to error, but a machine is not. In the field of autonomous vehicles, it emerged as a result of first the US media- and subsequently, stakeholders-demodalizing the results of a 2008 US National Highway Safety Administration study that claimed drivers were the critical cause of 94% of all road traffic accidents. In this article, we want to show what theoretical and socio-political problems exist with an explanation through the "human factor". To this end, we consider an alternative in the form of the concept of a technological system as a conflicting set of rules that follow the contextualizing practices proposed by the British sociologist Brian Wynne. We compare this interpretation with Robert Merton's explanation of deviant behavior in the 1930 s. Criticizing the utilitarians, Merton shows that deviations are caused by contradictions in the socio-cultural structure of society. In both conceptual schemes, failures are presented as the result of relational effects of tension and contradiction between the elements of the systems. For a different and more realistic alternative of dealing with accidents, we highlight the ideas of Annemarie Mol and John Law. The latter, analysing accidents, identified four modes of determining the good within disputes after accidents: mobile utopia, absolutism, managerialism, and practical manipulation. We show that both the explanations through the human factor, Merton's theory of deviation-and, to some extent, STS-lean towards utopian regimes (the first three), while the latter regime, based on an ontological turn, proposes a radical project of changing the modes of explanation and accusations of accidents: this makes it possible to articulate different relationships between the ontologies of accidents, to make non-utopian versions of technologies more real and public.